Systems and Methods for Determining and Utilizing Customer Energy Profiles for Load Control for Individual Structures, Devices, and Aggregation of Same

ABSTRACT

A system and method for creating and making use of customer profiles, including energy consumption patterns. Devices within a service point, using the active load director, may be subject to control events, often based on customer preferences. These control events cause the service point to use less power. Data associated with these control events, as well as related environment data, are used to create an energy consumption profile for each service point. This can be used by the utility to determine which service points are the best targets for energy consumption. In addition, an intelligent load rotation algorithm determines how to prevent the same service points from being picked first each time the utility wants to conserve power.

CROSS-REFERENCE TO RELATED APPLICATIONS

This non-provisional utility patent application claims priority from andis a continuation of U.S. application Ser. No. 13/464,665, filed May 4,2012, which is a continuation-in-part of U.S. application Ser. No.13/019,867, now U.S. Pat. No. 8,996,183, filed Feb. 2, 2011, and is acontinuation-in-part of U.S. application Ser. No. 12/896,307, now U.S.Pat. No. 8,527,107, filed on Oct. 1, 2010, which are bothcontinuations-in-part of U.S. application Ser. No. 12/702,640, now U.S.Pat. No. 8,131,403, filed Feb. 9, 2010, which is a continuation-in-partof U.S. application Ser. No. 11/895,909, now U.S. Pat. No. 7,715,951,filed Aug. 28, 2007, each of which is incorporated herein by referencein its entirety.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates generally to electrical power load controlsystems and, more particularly, to creating customer profiles usingenergy consumption patterns.

2. Description of Related Art

Customer profiles are often used by systems for a variety of reasons.One reason is to promote customer loyalty. This involves keepinginformation about not only the customer, but about the customer'sactions as well. This may include information about what the customerowns (i.e., which devices), how they are used, when they are used, etc.By mining this data, a company can more effectively select rewards forcustomers that give those customers an incentive for continuing to dobusiness with the company. This is often described as customerrelationship management (CRM).

Customer profile data is also useful for obtaining feedback about how aproduct is used. In software systems, this is often used to improve thecustomer/user experience or as an aid to testing. Deployed systems thathave customer profiling communicate customer actions and other data backto the development organization. That data is analyzed to understand thecustomer's experience. Lessons learned from that analysis is used tomake modifications to the deployed system, resulting in an improvedsystem.

Customer profile data may also be used in marketing and sales. Forinstance, a retail business may collect a variety of information about acustomer, including what customers look at on-line and inside“brick-and-mortar” stores. This data is mined to try to identifycustomer product preferences and shopping habits. Such data helps salesand marketing determine how to present products of probable interest tothe customer, resulting in greater sales.

However, the collection of customer profile information by powerutilities has been limited to customer account information. Becausepower utilities typically are unable to collect detailed data about whatis happening inside a customer's home or business, including patterns ofenergy consumption by device, there has been little opportunity tocreate extensive customer profiles.

SUMMARY OF THE INVENTION

Embodiments described herein utilize the Active Load Management System(ALMS) that is fully described in commonly-owned published patentapplication US 2009/0062970. The ALMS captures energy usage data at eachservice point and stores that data in a central database. This datadescribes all of the energy consumed by devices owned by each customer,as well as additional information, such as customer preferences. Otherembodiments of the ALMS focus on use of this information in thecalculation of carbon credits or for the trading of unused energy.

In one embodiment, a system and method are provided for creating andmaking use of customer profiles, including energy consumption patterns.Devices within a service point, using the active load director, may besubject to control events, often based on customer preferences. Thesecontrol events cause the service point to use less power. Dataassociated with these control events, as well as related environmentdata, are used to create an energy consumption profile for each servicepoint. This can be used by the utility to determine which service pointsare the best targets for energy consumption. In addition, an additionalalgorithm determines how to prevent the same service points from beingpicked first each time the utility wants to conserve power.

In one embodiment, a method is provided for determining and usingcustomer energy profiles to manage electrical load control events on acommunications network between a server in communication with anelectric utility and a client device at each of a plurality of servicepoints. A customer profile is generated at the server for each of aplurality of customers including at least energy consumption informationfor a plurality of controllable energy consuming devices at anassociated service point. The plurality of customer profiles is storedin a database at the server for use in load control events. Theplurality of customer profiles are aggregated into a plurality of groupsbased on at least one predetermined criterion. A candidate list ofservice points for load control events based on the predeterminedcriterion is generated at the server. A load control event is sent to atleast one selected service point in the candidate list of service pointsin response to an energy reduction request including a target energysavings received from the electric utility via the communicationsnetwork. An energy savings for the plurality of controllable energyconsuming devices resulting from the load control event at the selectedservice point is determined at the server. The server determines if theresulting energy savings is at least equal to the target energy savings.The load control event is sent to at least one selected additionalservice point in the candidate list of service points in order to reachthe target energy savings, if the target energy savings has not beenreached.

In one embodiment, a system is provided for determining and usingcustomer energy profiles to manage electrical load control events on acommunications network between a server in communication with anelectric utility and a client device at each of a plurality of servicepoints. The system includes a memory storing a database containing aplurality of customer profiles for load control events wherein eachcustomer profile includes at least energy consumption information for aplurality of controllable energy consuming devices at an associatedservice point; and a server processor, cooperative with the memory, andconfigured for managing electrical load control events on thecommunications network to the plurality of service points by: generatinga customer profile for each of a plurality of customers; aggregating theplurality of customer profiles into a plurality of groups based on atleast one predetermined criterion; generating a candidate list ofservice points for load control events based on the predeterminedcriterion; sending a load control event to at least one selected servicepoint in the candidate list of service points in response to an energyreduction request including a target energy savings received from theelectric utility via the communications network; determining an energysavings for the plurality of controllable energy consuming devicesresulting from the load control event at the selected service point;determining if the resulting energy savings is at least equal to thetarget energy savings; and sending the load control event to at leastone selected additional service point in the candidate list of servicepoints in order to reach the target energy savings.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other advantages and aspects of the embodiments of theinvention will become apparent and more readily appreciated from thefollowing detailed description of the embodiments taken in conjunctionwith the accompanying drawings, as follows.

FIG. 1 is a block diagram of an exemplary IP-based, Active LoadManagement System (ALMS).

FIG. 2 is a block diagram illustrating an exemplary active load director(ALD) server included in the active load management system.

FIG. 3 is a block diagram illustrating an exemplary active load client(ALC) included in the active load management system.

FIG. 4 is a graph illustrating how drift is calculated.

FIG. 5 is a graph illustrating how service points are selected foroptimal drift.

FIG. 6 is an operational flow diagram illustrating an exemplaryIntelligent Load Rotation algorithm.

DETAILED DESCRIPTION

Before describing in detail exemplary embodiments, it should be observedthat the embodiments described reside primarily in combinations ofapparatus components and processing steps related to actively managingpower loading on an individual subscriber or service point basis,determining the customer profile of individual devices aggregated torelated service points, and optionally tracking power savings incurredby both individual subscribers and an electric utility. Accordingly, theapparatus components and method steps have been represented whereappropriate by conventional symbols in the drawings, showing only thosespecific details that are pertinent to understanding the embodimentsdisclosed so as not to obscure the disclosure with details that will bereadily apparent to those of ordinary skill in the art having thebenefit of the description herein.

The term “electric utility” refers to any entity that generates anddistributes electrical power to its customers, that purchases power froma power-generating entity and distributes the purchased power to itscustomers, or that supplies electricity created by alternative energysources, such as solar power, wind power or otherwise, to powergeneration or distribution entities through the Federal EnergyRegulatory Commission (FERC) electrical grid or otherwise. The presentinvention provides for systems and methods relating to an electric gridoperator or any market participant associated with an electric grid,including retail electrical providers.

Embodiments of the invention include a number of novel concepts,including a customer profile, drift, and intelligent load rotation asmore fully described below. A customer profile captures patterns ofpower consumption for each customer. The drift concept includes a methodfor calculating drift, which is important in estimating power savingswithin thermal control devices. The intelligent load rotation conceptincludes a method for selecting customers for utility-initiated controlevents using intelligent load rotation.

The embodiments described utilize concepts disclosed in commonly-ownedpublished patent application US 2009/0062970, entitled “System andMethod for Active Power Load Management” which is incorporated byreference in its entirety herein. The following paragraphs describe theActive Management Load System (ALMS), Active Load Director (ALD), andActive Load Client (ALC) in sufficient detail to assist the reader inthe understanding of the embodiments described herein. More detaileddescription of the ALMS, ALD, and ALC can be found in US 2009/0062970.

It should be noted that control events and other messaging used inembodiments of the invention include regulated load management messages.Regulated load management messages contain information used to applycontrol of the electric supply to individual appliances or equipment oncustomer premises. The load to be controlled includes native load andoperating reserves including regulating, spinning, and non-spinningtypes.

Active Load Management System

FIG. 1 depicts an exemplary IP-based Active Load Management System(ALMS) 10 that may be utilized by a utility in the embodiments describedherein. The exemplary ALMS 10 monitors and manages power distributionvia an active load director (ALD) 100 connected between one or moreutility control centers (UCCs) 200 and one or more Active Load Clients(ALCs) 300. The ALD 100 may communicate with the utility control center200 and each active load client 300 either directly or through a network80 using the Internet Protocol (IP) or any other connection-basedprotocols. For example, the ALD 100 may communicate using RF systemsoperating via one or more base stations 90 using one or more well-knownwireless communication protocols. Alternatively, or additionally, theALD 100 may communicate via a digital subscriber line (DSL) capableconnection, cable television based IP capable connection, or anycombination thereof. In the exemplary embodiment shown in FIG. 1, theALD 100 communicates with one or more active load clients 300 using acombination of traditional IP-based communication (e.g., over a trunkedline) to a base station 90 and a wireless channel implementing the WiMaxprotocol for the “last mile” from the base station 90 to the active loadclient 300.

Each ALC 300 is accessible through a specified address (e.g., IPaddress) and controls and monitors the state of individual smart breakermodules or intelligent appliances 60 installed in the business orresidence 20 to which the ALC 300 is associated (e.g., connected orsupporting). Each ALC 300 is associated with a single residential orcommercial customer. In one embodiment, the ALC 300 communicates with aresidential load center 400 that contains smart breaker modules, whichare able to switch from an “ON” (active) state to an “OFF” (inactive)state, and vice versa, responsive to signaling from the ALC 300.Typically, each smart breaker controls a single appliance (e.g., awasher/dryer 30, a hot water heater 40, an HVAC unit 50, or a pool pump70).

Additionally, the ALC 300 may control individual smart appliancesdirectly (e.g., without communicating with the residential load center400) via one or more of a variety of known communication protocols(e.g., IP, Broadband over Power Line (BPL) in various forms, includingthrough specifications promulgated or being developed by the HOMEPLUGPowerline Alliance and the Institute of Electrical and ElectronicsEngineers (IEEE), Ethernet, Bluetooth, ZigBee, Wi-Fi, WiMax, etc.).Additionally or alternatively to WiMax, other communications protocolsmay be used, including but not limited to a “1G” wireless protocol suchas analog wireless transmission, first generation standards based (IEEE,ITU or other recognized world communications standard), a “2-G”standards based protocoal such as “EDGE or CDMA 2000 also known as1XRTT”, a 3G based standard such as “High Speed Packet Access (HSPA) orEvolution for Data Only (EVDO), any accepted 4G standard such as “IEEE,ITU standards that include WiMax, Long Term Evolution “LTE” and itsderivative standards, any Ethernet solution wireless or wired, or anyproprietary wireless or power line carrier standards that communicate toa client device or any controllable device that sends and receives an IPbased message.

Typically, a smart appliance 60 includes a power control module (notshown) having communication abilities. The power control module isinstalled in-line with the power supply to the appliance, between theactual appliance and the power source (e.g., the power control module isplugged into a power outlet at the home or business and the power cordfor the appliance is plugged into the power control module). Thus, whenthe power control module receives a command to turn off the appliance60, it disconnects the actual power supplying the appliance 60.Alternatively, a smart appliance 60 may include a power control moduleintegrated directly into the appliance, which may receive commands andcontrol the operation of the appliance directly (e.g., a smartthermostat may perform such functions as raising or lowering the settemperature, switching an HVAC unit on or off, or switching a fan on oroff).

Also as shown in FIG. 1, a service point 20 may have its own powergeneration on-site, including solar panels, fuel cells, or windturbines. This is indicated by the power generating device 96. The powergenerating device 96 connects to the Active Load Client 300. Power thatis added by the power generating device 96 is added to the overallutility capacity. The utility provides credit to the service point ownerbased on the energy produced at the service point.

The service point 20 also contains the Customer Dashboard 98. This is aweb-based interface used by the customer to specify preferences for theuse of the Active Load Management System at the customer's servicepoint. These preferences include control event preferences, billmanagement preferences, and others.

Active Load Director

Referring now to FIG. 2, the ALD 100 may serve as the primary interfaceto customers, as well as to service personnel. In the exemplaryembodiment depicted in FIG. 2, the ALD 100 includes a utility controlcenter (UCC) security interface 102, a UCC command processor 104, amaster event manager 106, an ALC manager 108, an ALC security interface110, an ALC interface 112, a web browser interface 114, a customersign-up application 116, customer personal settings 138, a customerreports application 118, a power savings application 120, an ALCdiagnostic manager 122, an ALD database 124, a service dispatch manager126, a trouble ticket generator 128, a call center manager 130, a carbonsavings application 132, a utility power and carbon database 134, a readmeter application 136, and a security device manager 140.

In one embodiment, customers interact with the ALD 100 using the webbrowser interface 114, and subscribe to some or all of the servicesoffered by the power load management system 10 via a customer sign-upapplication 116. In accordance with the customer sign-up application116, the customer specifies customer personal settings 138 that containinformation relating to the customer and the customer's residence orbusiness, and defines the extent of service to which the customer wishesto subscribe. Customers may also use the web browser interface 114 toaccess and modify information pertaining to their existing accounts.

The ALD 100 also includes a UCC security interface 102 which providessecurity and encryption between the ALD 100 and a utility company'scontrol center 200 to ensure that no third party is able to provideunauthorized directions to the ALD 100. A UCC command processor 104receives and sends messages between the ALD 100 and the utility controlcenter 200. Similarly, an ALC security interface 110 provides securityand encryption between the ALD 100 and each ALC 300 on the system 10,ensuring that no third parties can send directions to, or receiveinformation from, the ALC 300. The security techniques employed by theALC security interface 110 and the UCC security interface 102 mayinclude conventional symmetric key or asymmetric key algorithms, orproprietary encryption techniques.

The master event manager 106 maintains the overall status of the powerload activities controlled by the power management system 10. The masterevent manager 106 maintains a separate state for each utility that iscontrolled and tracks the current power usage within each utility. Themaster event manager 106 also tracks the management condition of eachutility (e.g., whether or not each utility is currently being managed).The master event manager 106 receives instructions in the form oftransaction requests from the UCC command processor 104 and routesinstructions to components necessary to complete the requestedtransaction, such as the ALC manager 108 and the power savingsapplication 120.

The ALC manager 108 routes instructions between the ALD 100 and each ALC300 within the system 10 through an ALC interface 112. For instance, theALC manager 108 tracks the state of every ALC 300 serviced by specifiedutilities by communicating with the ALC 300 through an individual IPaddress. The ALC interface 112 translates instructions (e.g.,transactions) received from the ALC manager 108 into the proper messagestructure understood by the targeted ALC 300 and then sends the messageto the ALC 300. Likewise, when the ALC interface 112 receives messagesfrom an ALC 300, it translates the message into a form understood by theALC manager 108 and routes the translated message to the ALC manager108.

The ALC manager 108 receives from each ALC 300 that it services, eitherperiodically or responsive to polling messages sent by the ALC manager108, messages containing the present power consumption and the status(e.g., “ON” or “OFF”) of each device controlled by the ALC 300.Alternatively, if individual device metering is not available, then thetotal power consumption and load management status for the entire ALC300 may be reported. The information contained in each status message isstored in the ALD database 124 in a record associated with the specifiedALC 300. The ALD database 124 contains all the information necessary tomanage every customer account and power distribution. In one embodiment,the ALD database 124 contains customer contact information andassociated utility companies for all customers having ALCs 300 installedat their residences or businesses, as well as a description of specificoperating instructions for each managed device (e.g., IP-addressablesmart breaker or appliance), device status, and device diagnostichistory.

Another message that can be exchanged between an ALC 300 and the ALCmanager 108 is a status response message. A status response messagereports the type and status of each device controlled by the ALC 300 tothe ALD 100. When a status response message is received from an ALC 300,the ALC manager 108 logs the information contained in the message in theALD database 124.

In one embodiment, upon receiving instructions (e.g., a “Cut”instruction) from the master event manager 106 to reduce powerconsumption for a specified utility, the ALC manager 108 determineswhich ALCs 300 and/or individually controlled devices to switch to the“OFF” state based upon present power consumption data stored in the ALDdatabase 124. The ALC manager 108 then sends a message to each selectedALC 300 containing instructions to turn off all or some of the devicesunder the ALC's control.

A read meter application 136 may be optionally invoked when the UCCcommand processor 104 receives a “Read Meters” or equivalent commandfrom the utility control center 200. The read meter application 136cycles through the ALD database 124 and sends a read meter message orcommand to each ALC 300, or to ALCs 300 specifically identified in theUCC's command, via the ALC manager 108. The information received by theALC manager 108 from the ALC 300 is logged in the ALD database 124 foreach customer. When all the ALC meter information has been received, theinformation is sent to the requesting utility control center 200 using abusiness to business (e.g., ebXML) or other desired protocol.

Active Load Client

FIG. 3 illustrates a block diagram of an exemplary active load client300 in accordance with one embodiment of the present invention. Thedepicted active load client 300 includes a smart breaker modulecontroller 306, a communications interface 308, a security interface310, an IP-based communication converter 312, a device control manager314, a smart breaker (B1-BN) counter manager 316, an IP router 320, asmart meter interface 322, a smart device interface 324, an IP deviceinterface 330, and a power dispatch device interface 340. The activeload client 300, in this embodiment, is a computer or processor-basedsystem located on-site at a customer's residence or business. Theprimary function of the active load client 300 is to manage the powerload levels of controllable, power consuming load devices located at theresidence or business, which the active load client 300 oversees onbehalf of the customer. In an exemplary embodiment, the active loadclient 300 may include dynamic host configuration protocol (DHCP) clientfunctionality to enable the active load client 300 to dynamicallyrequest IP addresses for itself and/or one or more controllable devices402-412, 60 managed thereby from a DHCP server on the host IP networkfacilitating communications between the active load client 300 and theALD 100. The active load client 300 may further include routerfunctionality and maintain a routing table of assigned IP addresses in amemory of the active load client 300 to facilitate delivery of messagesfrom the active load client 300 to the controllable devices 402-412, 60.Finally, the power generation device 96 at the service point 20 sendsdata about power generated to the power dispatch device interface 340.

A communications interface 308 facilitates connectivity between theactive load client 300 and the ALD server 100. Communication between theactive load client 300 and the ALD server 100 may be based on any typeof IP or other connection protocol including, but not limited to, theWiMax protocol. Thus, the communications interface 308 may be a wired orwireless modem, a wireless access point, or other appropriate interface.

A standard IP Layer-3 router 320 routes messages received by thecommunications interface 308 to both the active load client 300 and toany other locally connected device 440. The router 320 determines if areceived message is directed to the active load client 300 and, if so,passes the message to a security interface 310 to be decrypted. Thesecurity interface 310 provides protection for the contents of themessages exchanged between the ALD server 100 and the active load client300. The message content is encrypted and decrypted by the securityinterface 310 using, for example, a symmetric encryption key composed ofa combination of the IP address and GPS data for the active load client300 or any other combination of known information. If the message is notdirected to the active load client 300, then it is passed to the IPdevice interface 330 for delivery to one or more locally connecteddevices 440. For example, the IP router 320 may be programmed to routepower load management system messages as well as conventional Internetmessages. In such a case, the active load client 300 may function as agateway for Internet service supplied to the residence or businessinstead of using separate Internet gateways or routers.

An IP based communication converter 312 opens incoming messages from theALD server 100 and directs them to the appropriate function within theactive load client 300. The converter 312 also receives messages fromvarious active load client 300 functions (e.g., a device control manager314, a status response generator 304, and a report trigger application318), packages the messages in the form expected by the ALD server 100,and then passes them on to the security interface 310 for encryption.

The device control manager 314 processes power management commands forvarious controllable devices logically connected to the active loadclient 300. The devices can be either smart breakers 402-412 or other IPbased devices 60, 460, such as smart appliances with individual controlmodules (not shown). The device control manager 314 also processes“Query Request” or equivalent commands or messages from the ALD server100 by querying a status response generator 304 which maintains the typeand status of each device controlled by the active load client 300, andproviding the status of each device to the ALD server 100.

The status response generator 304 receives status messages from the ALDserver 100 and, responsive thereto, polls each controllable device402-412, 60, 460 under the active load client's control to determinewhether the controllable device 402-412, 60, 460 is active and in goodoperational order. Each controllable device 402-412, 60, 460 responds tothe polls with operational information (e.g., activity status and/orerror reports) in a status response message. The active load client 300stores the status responses in a memory associated with the statusresponse generator 304 for reference in connection with power reductionevents.

The smart device interface 324 facilitates IP or other address-basedcommunications to individual devices 60 (e.g., smart appliance powercontrol modules) that are attached to the active load client 300. Theconnectivity can be through one of several different types of networksincluding, but not limited to, BPL, ZigBee, Wi-Fi, Bluetooth, or directEthernet communications. Thus, the smart device interface 324 is a modemadapted for use in or on the network connecting the smart devices 60 tothe active load client 300.

The smart breaker module controller 306 formats, sends, and receivesmessages to and from the smart breaker module 400. In one embodiment,the communications is preferably through a BPL connection. In suchembodiment, the smart breaker module controller 306 includes a BPL modemand operations software. The smart breaker module 400 containsindividual smart breakers 402-412, wherein each smart breaker 402-412includes an applicable modem (e.g., a BPL modem when BPL is thenetworking technology employed) and is preferably in-line with powersupplied to a single appliance or other device. The B1-BN countermanager 316 determines and stores real time power usage for eachinstalled smart breaker 402-412. For example, the counter manager 316tracks or counts the amount of power used by each smart breaker 402-412and stores the counted amounts of power in a memory of the active loadclient 300 associated with the counter manager 316.

The smart meter interface 322 manages either smart meters 460 thatcommunicate using BPL or a current sensor 452 connected to a traditionalpower meter 450. When the active load client 300 receives a “ReadMeters” command or message from the ALD server 100 and a smart meter 460is attached to the active load client 300, a “Read Meters” command issent to the meter 460 via the smart meter interface 322 (e.g., a BPLmodem). The smart meter interface 322 receives a reply to the “ReadMeters” message from the smart meter 460, formats this information alongwith identification information for the active load client 300, andprovides the formatted message to the IP based communication converter312 for transmission to the ALD server 100.

Customer Profiles

The embodiments disclosed make use of the “customer profiles” concept.The ALMS enables data to be gathered to generate a profile of eachcustomer, including information about controllable energy consumingdevices, and the related individual structures or service points.Customer profiles reside within the Active Load Director Database 124 inthe Active Load Director 100. Included in this customer profile is thecustomer's pattern of energy consumption. The customer profile includes,but is not limited to, the following: (1) customer name; (2) customeraddress; (3) geodetic location; (4) meter ID; (5) customer programs(possibly including program history); (6) device information, includingdevice type and manufacturer/brand; (7) customer energy consumptionpatterns; and (8) connection and disconnection profile. Theconnection/disconnection profile can include service priority (i.e.,elderly, police, etc.) and disconnection instructions.

The customer profile is created by using data gathered from within theALMS. Data gathered or calculated includes, but is not be limited to,the following: (1) set points; (2) energy and average energy used in agiven time period; (3) energy and average energy saved in a given timeperiod; (4) drift time per unit temperature and average drift time; and(5) power time per unit temperature and average power time per unittemperature.

In other embodiments, additional data called “variability factors” maybe captured by the ALMS as part of the customer profile, including, butnot limited to, the following: (1) outside temperature, (2) sunlight,(3) humidity, (4) wind speed and direction, (5) elevation above sealevel, (6) orientation of the service point structure, (7) duty durationand percentage, (8) set point difference, (9) current and historic roomtemperature, (10) size of structure, (11) number of floors, (12) type ofconstruction (brick, wood, siding etc.) (13) color of structure, (14)type of roofing material and color, (15) construction surface ofstructure (built on turf, clay, cement, asphalt etc.), (16) land use(urban, suburban, rural), (17) latitude/longitude, (18) relativeposition to jet stream, (19) quality of power to devices, (20) number ofpeople living in and/or using structure and (21) other environmentalfactors.

Additional factors may also be deemed necessary for determining uniqueenergy consumption patterns and generating performance curves and datamatrices for usage in load control events and other purposes detailed inthis and related patent applications.

By way of example, based upon the reduction in consumed power, thesystems and methods of the present invention provide for generating atthe control center a power supply value (PSV) corresponding to thereduction in consumed power by the power consuming device(s).Importantly, the PSV is an actual value that includes measurement andverification of the reduction in consumed power; such measurement andverification methods may be determined by the appropriate governing bodyor authority for the electric power grid(s). Power Supply Value (PSV) iscalculated at the meter or submeter or at building control system or atany device or controller that measures power within the standard assupplied by the regulatory body(ies) that govern the regulation of thegrid. PSV variations may depend on operating tolerances, operatingstandard for accuracy of the measurement. The PSV enables transformationof curtailment or reduction in power at the device level by any systemthat sends or receives an IP message to be related to or equated tosupply as presented to the governing entity that accepts these valuesand award supply equivalence, for example of a power generating entityor an entity allowed to control power consuming devices as permitted bythe governing body of the electric power grid, e.g., FERC, NERC, etc.

PSV may be provided in units of electrical power flow, monetaryequivalent, and combinations thereof. Thus, the PSV provides an actualvalue that is confirmed by measurement and/or verification, therebyproviding for a curtailment value as a requirement for providing supplyto the power grid, wherein the supply to the power electric power gridis provided for grid stability, voltage stability, reliability, andcombinations thereof, and is further provided as responsive to an energymanagement system or equivalent for providing grid stability,reliability, frequency as determined by governing authority for theelectric power grid and/or grid operator(s).

As part of the Active Load Directory (ALD), the methods described hereinconsolidate this information creating a historic energy consumptionpattern reflecting the amount of energy used by each service point tomaintain its normal mode of operation. This energy consumption patternis part of a customer's profile.

Energy consumption patterns are subject to analysis that may be used fora variety of different types of activities. For example, based on theenergy consumption patterns created from this data, the ALD will deriveperformance curves and/or data matrices for each service point to whichthe Active Load Management System is attached and determine the amountof energy reduction that can be realized from each service point. TheALD will create a list of service points through which energyconsumption can be reduced via demand side management, interruptibleload, or spinning/regulation reserves. This information can bemanipulated by the ALD processes to create a prioritized, rotationalorder of control, called “intelligent load rotation” which is describedin detail below. This rotational shifting of the burden of theinterruptible load has the practical effect of reducing and flatteningthe utility load curve while allowing the serving utility to effectivelygroup its customers within the ALD or its own databases by energyefficiency.

The practical application of this data is that in load control events, autility can determine the most efficient service points to dispatchenergy from, or more importantly derive the most inefficient servicepoints (e.g., homes, small businesses, communities, structures, ordevices) within the utility's operating territory. Based on thisinformation, highly targeted conservation programs could have animmediate impact to improve energy efficiency. From a marketingperspective, this is invaluable information because it contains thecomfort preference of a service point compared against the capabilitiesof the service point's energy consuming devices, or the lack ofefficiency of those devices. From a national security point of view, theprofiles could be used to determine habits of monitored end customers ina similar fashion to how Communications Assistance for Law EnforcementAct (CALEA) is used by law enforcement for wire-tapping. Utilities mayuse energy consumption patterns to categorize or group customers forservice, control event, marketing, sales, or other purposes. Other usesof energy consumption patterns are possible that determine or predictcustomer behavior.

Generally, the embodiments described encompass a closed loop system andmethod for creating a customer profile, calculating and derivingpatterns of energy drift, and making use of those patterns whenimplemented through the machinery of a system comprised of loadmeasurement devices combined with the physical communications link andwhen these inputs are manipulated through a computer, processor, memory,routers and other necessary machines as those who are skilled in the artwould expect to be utilized.

Drift

The embodiments described also make use of the concept of “drift.” Thedata gathered for the customer profile is used to empirically derive thedecay rate or drift, temperature slope, or a dynamic equation (f{x})whereby the service point (or device) will have a uniquely derived“fingerprint” or energy usage pattern.

Drift occurs when a climate-controlled device begins to deviate from aset point. This may occur both normally and during control events.Customers define the upper and lower boundaries of comfort in customerpreferences, with the set point in the middle of those boundaries.During normal operation, a climate controlled device will attempt tostay near the device's set point. However, all devices have a duty cyclethat specifies when the device is in operation because many devices arenot continuously in operation. For a climate-controlled device, the dutycycle ends when the inside temperature reaches, or is within a giventolerance of, the set point. This allows the device to “drift” (upwardor downward) toward a comfort boundary temperature. Once the boundarytemperature is reached, the duty cycle begins again until the insidetemperature reaches, or is within a given tolerance of, the set pointwhich ends the duty cycle.

Therefore, drift is the time it takes for a climate-controlled device tomove from the set point to the upper or lower comfort boundary. Drift iscalculated and recorded for each service point and for each deviceassociated with the service point. The inverse of drift is “power time”which is the time it takes for the device to move from the comfortboundary to the set point.

Drift may also occur during a control event. A control event is anaction that reduces or terminates power consumption of a device. Duringa control event, a climate-controlled device will drift toward maximumor minimum control event boundaries (upper or lower) until it reachesthat boundary which is normally outside the comfort boundary. Once itreaches the control event boundary, the ALMS returns power to the deviceto enable it to reach the set point again.

As an example, an HVAC system may have a set point of 72 degrees and aminimum and maximum temperature of 68 degrees and 76 degrees,respectively. On a cold day, a control event would cause the HVAC systemto begin to lose power and move toward the minimum temperature. Once thestructure reaches the minimum temperature, the control event would end,and power would be restored to the HVAC system, thus causing thetemperature to rise toward the preferred temperature. A similar butopposite effect would take place on a warm day.

In some embodiments, drift, as well as other measurements available fromthe active load director data base 124, are used to create an energyconsumption pattern for each service point. Additional measurements mayinclude vacancy times, sleep times, times in which control events arepermitted, as well as variability factors referred to previously.

A device that resides within an energy-efficient structure will have atendency to cool or heat more slowly, thus exhibiting a lower rate ofdrift. These devices may be subject to control events for longer periodsof time, commensurate with the rate of drift, because it takes themlonger to drift to a comfort boundary.

In another embodiment, the active load director server 100 identifiesservice points that have an optimum drift for power savings. The powersavings application 120 calculates drift for each service point andsaves that information in the active load director data base 124.

Intelligent Load Rotation

The embodiments disclosed also make use of the “intelligent loadrotation” concept. Intelligent load rotation uses machine intelligenceto ensure that the same service points are not always selected forcontrol events, but distributes control events over a service area insome equitable way.

There are a variety of ways in which intelligent load rotation may beimplemented. In one embodiment of intelligent load rotation, servicepoints are simply selected in a sequential list until the end isreached, after which selection starts at the top of the list again. Thisis a fairly straightforward approach that may be implemented by any oneskilled in the art.

FIG. 6 illustrates an operational flow diagram of the basic intelligentload rotation algorithm 1800. All other embodiments of intelligent loadrotation are based on this embodiment. In general, the algorithm goesthrough each service point within a group of service points, and sendscontrol events to each of those service points until enough energysavings have been obtained.

In its most basic form, the algorithm first identifies a group selectioncriteria as indicated in logic block 1802. This may be as simple as allservice points or may be more complex, such as selecting service pointswithin a specified drift or within a specified geographic area. Thegroup selection criteria may include, but is not limited to, any of thefollowing: (1) random selection of service points; (2) drift; (3)grouping of logical geodetic points by a utility; (4) efficiency ratingof appliances; (5) ALD customer preferences; (6) capacity of devices;(7) proximity to transmission lines; (8) pricing signals (both dynamicand static); and (9) service priority, based upon an emergency situation(i.e. fire, police, hospital, elderly, etc.).

The algorithm then identifies an individual service point selectioncriterion as indicated in logic block 1804. This is the criterion forselecting individual service points within a group. In its simplestembodiment, this criterion involves sequential selection of servicepoints within the group. Other criteria may include random selection,selection based on number of previous control events, or other criteria.

Next, the algorithm creates a candidate list of service points based onthe group selection criteria as indicated in logic block 1806. From thislist, the algorithm selects a service point based on the individualservice point selection criteria as indicated in logic block 1810. TheALMS then sends a control event to the selected service point asindicated in logic block 1814, and calculates the energy savings of thatcontrol event based on drift calculation as indicated in block 1816. Thealgorithm then determines if more energy savings are needed to reach thesavings target as indicated in decision block 1820. If not, then theALMS records where the algorithm ended in the candidate list asindicated in block 1824 and exits. If more energy savings are needed,then the ALMS determines if any more service points are in the candidatelist as indicated in decision block 1830. If there are no more servicepoints in the candidate list, then the algorithm returns to thebeginning of the candidate list again in logic block 1840. Otherwise, ifthere are more service points in the candidate list, the algorithmsimply returns to logic block 1810.

In an alternate embodiment, decision block 1820 may be modified todetermine if more service points are to be selected from this group.

There are many other embodiments of intelligent load rotation. Manyembodiments are based on the group selection criteria. Service pointsmay be grouped by geography or some other common characteristic ofservice points. For example, groups might include “light consumers”(because they consume little energy), “daytime consumers” (because theywork at night), “swimmers” (for those who have a pool and use it), orother categories. These categories are useful to the utility for quicklyreferring to customers with specific energy demographics. The utilitymay then select a number of service points in each group for controlevents to spread control events among various groups.

In another embodiment, optimum drift can be used as the group selectioncriteria. Because those service points will use the least energy, theutility may want to select those service points that are the most energyefficient.

In another embodiment, a group of service points is selected that havehad the fewest control events in the past. This ensures that servicepoints with the most control events in the past will be bypassed infavor of those who have received fewer control events.

In another embodiment, with reference to FIGS. 4-5, drift is used as ameans of intelligent load rotation. As data is collected by the ALMS, itis possible to calculate the total drift of a device over time, as shownin FIG. 4. The calculation for one service point represents one vectoron the graph. Each vector represents the drift for a single servicepoint. To identify the service points with the optimal drift, the ALD100 determines the median drift and all service points having a driftthat is within one standard deviation away from that median. Thatrepresents the shaded area in the graph depicted in FIG. 5. Ifsufficient service points cannot be found that are within one standarddeviation, then the second standard deviation can be selected.

In another embodiment, energy consumption patterns in customer profilesare used to identify service points that are the best targets for excesspower sharing. This would occur when renewable energy such as solar orwind is added to the grid, resulting in power that cannot be compensatedfor by the grid. This could occur, for example, on very windy days. Whenthis happens, utilities are faced with the problem of what to do withthe excess energy. Instead of cutting power to service points in orderto affect power savings, a utility could add energy to service points inorder to effect power dissipation. The service points selected by theutility may be different (or even the inverse) of those selected forpower savings. The devices at these service points would be turned on ifthey were off or set points for climate-controlled devices would beadjusted to heat or cool more than normal. Spread out over many controlpoints, this can provide the energy dissipation needed.

In a further embodiment, energy consumption patterns within customerprofiles could be used to identify opportunities for up selling, downselling, or cross selling. These opportunities may be determined by thepower utility or by its partners. Data from customer profiles may beused to provide insights on inefficient devices, defective devices, ordevices that require updating to meet current standards. Customerprofile data may also be used to identify related sales opportunities.For example, if energy consumption patterns suggest that the customermay be very interested in personal energy conservation, then salesefforts could be directed toward that individual concerning productsrelated to that lifestyle. This information can be used by the utilityor its partners to provide incentives to customers to buy newer, updateddevices, or obtain maintenance for existing devices. The customer isgiven the option to opt out of having his customer profile used forsales and marketing efforts, or for regulating energy conservation. Thecustomer profile makes use of open standards (such as the CPExchangestandard) that specify a privacy model with the customer profile. Theuse of consumption patterns in this manner is governed by national,state, or local privacy laws and regulations.

A further embodiment of using customer profiles to identify salesopportunities involves the use of device information to createincentives for customers to replace inefficient devices. By identifyingthe known characteristics and/or behavior of devices within a servicepoint, the invention identifies those customers who may benefit fromreplacement of those devices. The invention estimates a payback periodfor replacement. This information is used by the ALMS operator to createredemptions, discounts, and campaigns to persuade customers to replacetheir devices.

It should be noted that many terms and acronyms are used in thisdescription that are well-defined in the telecommunications and computernetworking industries and are well understood by persons skilled inthese arts. Complete descriptions of these terms and acronyms, whetherdefining a telecommunications standard or protocol, can be found inreadily available telecommunications standards and literature and arenot described in any detail herein.

As used in the foregoing description, the term “ZigBee” refers to anywireless communication protocol adopted by the Institute of Electricaland Electronics Engineers (IEEE) according to standard 802.15.4 or anysuccessor standard(s), and the term “Bluetooth” refers to anyshort-range communication protocol implementing IEEE standard 802.15.1or any successor standard(s). The term “High Speed Packet Data Access(HSPA)” refers to any communication protocol adopted by theInternational Telecommunication Union (ITU) or another mobiletelecommunications standards body referring to the evolution of theGlobal System for Mobile Communications (GSM) standard beyond its thirdgeneration Universal Mobile Telecommunications System (UMTS) protocols.The term “Long Term Evolution (LTE)” refers to any communicationprotocol adopted by the ITU or another mobile telecommunicationsstandards body referring to the evolution of GSM-based networks tovoice, video and data standards anticipated to be replacement protocolsfor HSPA. The term “Code Division Multiple Access (CDMA) EvolutionDate-Optimized (EVDO) Revision A (CDMA EVDO Rev. A)” refers to thecommunication protocol adopted by the ITU under standard number TIA-856Rev. A.

It will be appreciated that embodiments or components of the systemsdescribed herein may be comprised of one or more conventional processorsand unique stored program instructions that control the one or moreprocessors to implement, in conjunction with certain non-processorcircuits, some, most, or all of the functions for managing power loaddistribution, and tracking and controlling individual subscriber powerconsumption and savings in one or more power load management systems.The non-processor circuits may include, but are not limited to, radioreceivers, radio transmitters, antennas, modems, signal drivers, clockcircuits, power source circuits, relays, meters, smart breakers, currentsensors, and customer input devices. As such, these functions may beinterpreted as steps of a method to distribute information and controlsignals between devices in a power load management system.Alternatively, some or all functions could be implemented by a statemachine that has no stored program instructions, or in one or moreapplication specific integrated circuits (ASICs), in which each functionor some combinations of functions are implemented as custom logic. Ofcourse, a combination of the two approaches could be used. Thus, methodsand means for these functions have been described herein. Further, it isexpected that one of ordinary skill in the art, notwithstanding possiblysignificant effort and many design choices motivated by, for example,available time, current technology, and economic considerations, whenguided by the concepts and principles disclosed herein, will be readilycapable of generating such software instructions, programs andintegrated circuits (ICs), and appropriately arranging and functionallyintegrating such non-processor circuits, without undue experimentation.

In the foregoing specification, the invention has been described withreference to specific embodiments. However, one of ordinary skill in theart will appreciate that various modifications and changes may be madewithout departing from the scope of the present invention as set forthin the appended claims. Accordingly, the specification and drawings areto be regarded in an illustrative rather than a restrictive sense, andall such modifications are intended to be included within the scope ofthe present invention.

The corresponding structures, materials, acts, and equivalents of allmeans plus function elements in any claims below are intended to includeany structure, material, or acts for performing the function incombination with other claim elements as specifically claimed.

In addition, it is possible to use some of the features of theembodiments disclosed without the corresponding use of the otherfeatures. Accordingly, the foregoing description of the exemplaryembodiments is provided for the purpose of illustrating the principlesof the invention, and not in limitation thereof, since the scope of thepresent invention is defined solely by the appended claims.

What is claimed is:
 1. A method for determining and using customerenergy profiles to manage electrical load control events on acommunications network between a server in communication with anelectric grid operator or any market participant associated with anelectric grid and a client device at each of a plurality of servicepoints, comprising the steps of: generating at the server, a customerprofile for each of a plurality of customers including at least energyconsumption information for a plurality of controllable temperaturecontrol devices or building control systems at an associated servicepoint; storing the plurality of customer profiles in a database at theserver for use in load control events; aggregating the plurality ofcustomer profiles into a plurality of groups based on at least onepredetermined criterion; generating at the server, a candidate list ofservice points for load control events based on the predeterminedcriterion; sending a load control event to at least one selected servicepoint in the candidate list of service points in response to an energyreduction request including a target energy savings received from theelectric grid operator or any market participant associated with anelectric grid via the communications network; determining at the server,an energy savings for the plurality of controllable energy consumingdevices resulting from the reduction in consumed power associated withthe load control event at the selected service point, wherein the energysavings is determined by a measurement and a verification of thereduction in consumed power equivalent to a market value for suppliedpower at that time; and determining at the server, if the resultingenergy savings is at least equal to the target energy savings.
 2. Themethod of claim 1, further including the step of the transforming themeasurement and the verification of the reduction in consumed power intoa power supply value (PSV) corresponding to each of the plurality ofcontrollable temperature control devices or building control systemsinto an aggregate power supply value.
 3. The method of claim 2, furtherincluding the step of associating the aggregate power supply value withthe aggregated customer profiles.
 4. The method of claim 1, wherein theenergy consumption information in each customer profile includes atleast one of a set point for a climate-controlled device, an energy usein a specified time period, an energy savings in a specified timeperiod, a drift time per unit temperature, a power time per unittemperature.
 5. The method of claim 1, wherein the customer profile foreach of the plurality of customers further includes a plurality ofvariability factors resulting in a unique energy consumption pattern atthe associated service point.
 6. The method of claim 1, furthercomprising determining a drift associated with each service point,wherein the drift is an amount of time for a climate-controlled deviceto move from a set point temperature to an upper or lower temperatureboundary defined in the customer profile.
 7. The method of claim 1,further comprising determining a power time associated with each servicepoint, wherein the power time is an amount of time for aclimate-controlled device to move from an upper or lower temperatureboundary defined in the customer profile to a set point temperature. 8.The method of claim 7, wherein the set point is a temperature that is amidpoint between an upper and a lower temperature boundary defined inthe customer profile for control events.
 9. The method of claim 1,wherein a temperature associated with a climate-controlled device at theselected service point drifts towards a maximum or minimum temperatureboundary during the load control event.
 10. The method of claim 9,further comprising returning power to the climate-controlled device wheneither a maximum or a minimum temperature boundary is reached.
 11. Themethod of claim 1, further comprising generating an energy consumptionpattern for each service point that reflects an amount of energy used byeach service point to maintain a normal mode of operation.
 12. Themethod of claim 11, further comprising deriving a performance curve foreach service point, and determining an amount of energy reduction thatcan be realized from the load control event at each service point. 13.The method of claim 1, further including the step of sending the loadcontrol event to at least one selected additional service point in thecandidate list of service points in order to reach the target energysavings.
 14. The method of claim 1, further comprising determining aindividual service point selection criterion for each of a plurality ofservice points aggregated into each group.
 15. The method of claim 1,wherein the predetermined criterion for aggregating the plurality ofcustomer profiles into the plurality of groups includes any one of arandom selection, a drift factor, a logical geodetic point, anefficiency rating for each controllable temperature control device at anassociated service point, a customer preference, a proximity to atransmission line, a pricing signal, and a priority for an emergencysituation.
 16. The method of claim 1, wherein the customer profilefurther includes identification of any power generating device at theassociated service point that can be added to an electrical power gridin response to a load control event sent to the service point.
 17. Themethod of claim 1, wherein the customer profile for each of theplurality of customers further includes at least one of a customer name,a customer address, a meter identifier, and controllable temperaturedevice information for each of the plurality of energy consuming devicesat the service point.
 18. The method of claim 1, further comprisingapplying the load control event to a controllable temperature controldevice at the service point having a low rate of drift, wherein thedrift is an amount of time for a climate-controlled device to move froma set point temperature to an upper or lower temperature boundarydefined in the customer profile.
 19. The method of claim 18, furthercomprising applying the load control event to a controllable energyconsuming device at the service point for a time that is commensuratewith the rate of drift.
 20. A system for determining and using customerenergy profiles to manage electrical load control events on acommunications network between a server in communication with anelectric grid operator or any market participant associated with anelectric grid and a client device at each of a plurality of servicepoints, comprising: a memory storing a database containing a pluralityof customer profiles for load control events wherein each customerprofile includes at least energy consumption information for a pluralityof controllable temperature control devices at an associated servicepoint; a server processor, cooperative with the memory, and configuredfor managing electrical load control events on the communicationsnetwork to the plurality of service points by: generating a customerprofile for each of a plurality of customers; aggregating the pluralityof customer profiles into a plurality of groups based on at least onepredetermined criterion; generating a candidate list of service pointsfor load control events based on the predetermined criterion; sending aload control event to at least one selected service point in thecandidate list of service points in response to an energy reductionrequest including a target energy savings received from the electricgrid operator or any market participant associated with an electric gridvia the communications network; determining an energy savings for theplurality of controllable energy consuming devices resulting from theload control event at the selected service point, wherein the energysavings is determined using a measurement and a verification of thereduction in consumed power corresponding to each of the plurality ofcontrollable temperature control devices or building control systems forproviding a monetary equivalent to supply for the reduction in theconsumed power; determining if the resulting energy savings is at leastequal to the target energy savings.
 21. The system of claim 20, whereinthe reduction in consumed power associated with the load control eventfor a load to be controlled includes native load and/or operatingreserves including regulating, spinning, and non-spinning types.
 22. Thesystem of claim 21, wherein the measurement and the verification istransformed into a power supply value corresponding to each of theplurality of controllable temperature control devices, is transformedinto an aggregate power supply value.
 23. The system of claim 21,wherein the power supply value for each of the at least one controllabletemperature control devices is transformed into an aggregate powersupply value that is compared to the target energy savings for the loadcontrol event.
 24. The system of claim 21, wherein the processor isfurther configured for associating the aggregate power supply value withthe aggregated customer profiles.
 25. The system of claim 20, whereinthe processor is further configured for selecting the at least oneservice point based on an individual service point criterion for each ofa plurality of service points aggregated into each group.
 26. The systemof claim 20 wherein the predetermined criterion for aggregating theplurality of customer profiles into the plurality of groups includes anyone of a random selection, a drift factor, a logical geodetic point, anefficiency rating for each controllable energy consuming device at anassociated service point, a customer preference, a proximity to atransmission line, a pricing signal, and a priority for an emergencysituation.